“…See the account in the book [3], and for more recent developments, the survey paper [5]. The min-max result states, and let us here restrict to finite dimensional selfadjoint (e.g., symmetric or Hermitian) positive operators A such as those we will treat in this paper, that…”
Section: Brief Backgroundmentioning
confidence: 99%
“…The operator trigonometry has other facets of course and a number of interesting applications to numerical analysis, statistics, Bell's inequalities, among others. We refer the reader to [3][4][5] and other papers we may cite in the course of this paper, for further information. But to help the reader for whom my operator trigonometry is new, let me mention three useful insights.…”
Section: Brief Backgroundmentioning
confidence: 99%
“…Using this 6 × 6 example, we point out that one could also consider the higher antieigenvalues and the corresponding smaller internal turning angles (see [5,12]) for ρ AB and its partial transpose with respect to A and the other examples treated in [11], should those be of interest. For example the subspace turning angle of the partial transpose matrix corresponding to the eigenvalues 1/4 and 1/8 is φ(1/4, 1/8) = sin −1 (1/3), no matter what the value of the noise coupler x.…”
Section: Disentanglement and Decoherencementioning
confidence: 99%
“…And the average turning angles are not really the actual geometrical critical turning angles of the operator. There is much more information in all the internal turning angles defined by my higher antieigenvalues and higher antieigenvectors [5,12].…”
Recently the geometry of quantum states has been under considerable development. Every good geometry deserves, if possible, an accompanying trigonometry. I will here introduce such a trigonometry to accompany the geometry of quantum states.
“…See the account in the book [3], and for more recent developments, the survey paper [5]. The min-max result states, and let us here restrict to finite dimensional selfadjoint (e.g., symmetric or Hermitian) positive operators A such as those we will treat in this paper, that…”
Section: Brief Backgroundmentioning
confidence: 99%
“…The operator trigonometry has other facets of course and a number of interesting applications to numerical analysis, statistics, Bell's inequalities, among others. We refer the reader to [3][4][5] and other papers we may cite in the course of this paper, for further information. But to help the reader for whom my operator trigonometry is new, let me mention three useful insights.…”
Section: Brief Backgroundmentioning
confidence: 99%
“…Using this 6 × 6 example, we point out that one could also consider the higher antieigenvalues and the corresponding smaller internal turning angles (see [5,12]) for ρ AB and its partial transpose with respect to A and the other examples treated in [11], should those be of interest. For example the subspace turning angle of the partial transpose matrix corresponding to the eigenvalues 1/4 and 1/8 is φ(1/4, 1/8) = sin −1 (1/3), no matter what the value of the noise coupler x.…”
Section: Disentanglement and Decoherencementioning
confidence: 99%
“…And the average turning angles are not really the actual geometrical critical turning angles of the operator. There is much more information in all the internal turning angles defined by my higher antieigenvalues and higher antieigenvectors [5,12].…”
Recently the geometry of quantum states has been under considerable development. Every good geometry deserves, if possible, an accompanying trigonometry. I will here introduce such a trigonometry to accompany the geometry of quantum states.
“…Further theoretical background for the matrix trigonometry may be found in the books Gustafson (1997), Gustafson & Rao (1997), and the papers cited in the bibliography here. Also a recent review is given in Gustafson (2006). The reader is referred to those sources for the terminology (all due to this author) to be used in this exposition.…”
A matrix trigonometry developed chiefly by this author during the past 40 years has interesting applications to certain situations in statistics. The key conceptual entity in this matrix trigonometry is the matrix (maximal) turning angle. Associated entities (originally so-named by this author) are the matrix antieigenvalues and corresponding antieigenvectors upon which the matrix obtains its critical turning angles. Because this trigonometry is the natural one for linear operators and matrices, it also is the natural one for matrix statistics.
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